Rethinking neglected tropical disease prevalence survey design and analysis: a geospatial paradigm. (15th February 2021)

• Record Type: Journal Article
• Authors: Diggle, Peter J; Amoah, Benjamin; Fronterre, Claudio; Giorgi, Emanuele; Johnson, Olatunji
• Is Part Of: Transactions of the Royal Society of Tropical Medicine and Hygiene. Volume 115:Number 3(2021)
• Page Start: 208
• Page End: 210
• Publication Date: 2021-02-15
• Subjects: elimination surveys -- geospatial methods -- predictive inference -- prevalence mapping; Tropical medicine -- Periodicals; 616.9883
• DOI: 10.1093/trstmh/trab020
• Languages: English
• ISSNs: 0035-9203

Abstract

Abstract: Current methods for the design and analysis of neglected tropical disease prevalence surveys largely rely on classical survey sampling ideas that treat prevalence data from different locations as an independent random sample from the probability distribution induced by a random sampling design. We set out an alternative, explicitly geospatial paradigm that can deliver much more precise estimates of the geospatial variation in prevalence over a country or region of interest. We describe the advantages of this approach under three headings: streamlining, whereby more precise results can be obtained with smaller sample sizes; integrating, whereby a joint analysis of data from two or more diseases can bring further gains in precision; and adapting, whereby the choice of future sampling location is informed by past data.